This paper presents a Discrete-Time Variable-Structure Control (DTVSC) for the dynamic positioning system of a marine supply vessel. The DTVSC guarantees robustness with respect to disturbances and parametric variations. Two wave-filtering approaches are employed: the Extended Kalman filter (EKF) and the multi-rate Kalman filter (MREKF) . The proposed solution is compared with a PID-based contr...

This paper is concerned with the state estimation problem in nonlinear fractional order discrete state-space systems with uncertain observations, when the random interruptions in the observation process are modelled by independent Bernoulli random variables. Two filtering algorithms are proposed for this class of systems; the first one is a generalization of the extended fractional Kalman filte...

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In this paper we investigates time delay and channel gain estimation for multipath fading Code Division Multiple Access (CDMA) signals using the second order Divided Difference Filter (DDF). Given the nonlinear dependency of the channel parameters on the received signals in multiuser/multipath scenarios, we show that the DDF achieves better performance than its linear counterparts. The DDF, whi...

Simultaneous Localization and Map Building (SLAM) is one of the fundamental problems in robot navigation. The Extended Kalman Filter (EKF), which is widely adopted in SLAM approaches, requires extensive computation. The conventional particle filter also needs intense computation to cover a high dimensional state space with particles. This paper proposes an efficient SLAM method based on the rec...

This paper presents filtering solutions for estimating the relative trajectory of a spin stabilized satellite. The SPHERES satellites have been selected as the hardware testbed for implementing a Multiplicative Extended Kalman Filter and novel Multiplicative Unscented Kalman Filter. Relative state measurements are provided by imaging fiducial markers on the target. The results from this analysi...

Abstract: This paper presents an application of nonlinear filtering techniques for the tracking control design of tracked mobile robot under slip condition. The slip is represented only by the longitudinal wheels slip that is described by just an unknown parameter. The extended Kalman filter (EKF), the unscented Kalman filter (UKF) and the particle filter (PF) are used to estimate the states of...

The problem of estimating unobserved states of spatially extended dynamical systems poses an inverse problem, which can be solved approximately by a recently developed variant of Kalman filtering; in order to provide the model of the dynamics with more flexibility with respect to space and time, we suggest to combine the concept of GARCH modelling of covariance, well known in econometrics, with...

In the several past years, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) havebecame basic algorithm for state-variables and parameters estimation of discrete nonlinear systems.The UKF has consistently outperformed for estimation. Sometimes least estimation error doesn't yieldwith UKF for the most nonlinear systems. In this paper, we use a new approach for a two variablestate no...

This paper is concerned with filtering nonlinear multivariate time series. A new approximate Bayesian algorithm is proposed which generates sample points and corresponding probability weights that match exactly the predicted values of average marginal skewness and average marginal kurtosis of the unobserved state variables, in addition to matching their mean and the covariance matrix. The perfo...